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Elkon, R.

Publications and source records attributed to Elkon, R..

2 recordsLinked to original sources

Genomic meta-analysis of the interplay between 3D chromatin organization and gene expression programs under basal and stress conditions

BackgroundOur appreciation of the critical role of the 3D organization of the genome in gene regulation is steadily increasing. Recent 3C-based deep sequencing techniques elucidated a hierarchy of structures that underlie the spatial organization of the genome in the nucleus. At the top of this hierarchical organization are chromosomal territories and the megabase-scale A/B compartments that correlate with transcriptional activity within cells. Below them are the relatively cell-type invariant topologically associated domains (TADs), characterized by high frequency of physical contacts between loci within the same TAD and are assumed to function as regulatory units. Within TADs, chromatin loops bring enhancers and target promoters to close spatial proximity. Yet, we still have only rudimentary understanding how differences in chromatin organization between different cell types affect cell-type specific gene expression programs that are executed under basal and challenged conditions.\n\nResultsHere, we carried out a large-scale meta-analysis that integrated Hi-C data from thirteen different cell lines and dozens of ChIP-seq and RNA-seq datasets measured on these cells, either under basal conditions or after treatment. Pairwise comparisons between cell lines demonstrated the strong association between modulation of A/B compartmentalization, differential gene expression and transcription factor (TF) binding events. Furthermore, integrating the analysis of transcriptomes of different cell lines in response to various challenges, we show that 3D organization of cells under basal conditions constrains not only gene expression programs and TF binding profiles that are active under the basal condition but also those induced in response to treatment.\n\nConclusionsOur results further elucidate the role of dynamic genome organization in regulation of differential gene expression between different cell types, and indicate the impact of intra-TAD enhancer-promoter interactions that are established under basal conditions on both the basal and treatment-induced gene expression programs.

genomics

An extensive enhancer-promoter map generated by genome-scale analysis of enhancer and gene activity patterns

Massive efforts have documented hundreds of thousands of putative enhancers in the human genome. A pressing genomic challenge is to identify which of these enhancers are functional and map them to the genes they regulate. We developed a novel method for inferring enhancer-promoter (E-P) links based on correlated activity patterns across many samples. Our method, called FOCS, uses rigorous statistical validation tailored for zero-inflated data, identifying the most important E-P links in each gene model. We applied FOCS to the wide epigenomic and transcriptomic datasets recorded by the ENCODE, Roadmap Epigenomics and FANTOM5 projects, together covering 2,630 samples of human primary cells, tissues and cell lines. In addition, building on expression of enhancer RNAs (eRNAs) as an exquisite mark of enhancer activity and on the robust detection of eRNAs by the GRO-seq technique, we compiled a compendium of eRNA and gene expression profiles based on public GRO-seq data from 245 samples and 23 human cell types. Applying FOCS to this compendium further expanded the coverage of our inferred E-P map. Benchmarking against gold standard E-P links from ChIA-PET and eQTL data, we demonstrate that FOCS prediction of E-P links outperforms extant methods. Collectively, we inferred >300,000 cross-validated E-P links spanning ~16K known genes. Our study presents an improved method for inferring regulatory links between enhancers and promoters, and provides an extensive resource of E-P maps that could greatly assist the functional interpretation of the noncoding regulatory genome. FOCS and our predicted E-P map are publicly available at http://acgt.cs.tau.ac.il/focs.

bioinformatics